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Python scripts to make maps of spectral parameters with Chandra data

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Xmaps

Python scripts to make maps of spectral parameters with Chandra data.

The make_maps.py script will extract and fit spectra from regions defined in an input binmap. The binmap is simply a FITS image with the values that lie in each bin equal to the bin's number. Binmaps can be generated in a number of ways, such as with the Contbin algorithm of Sanders (2006) or the WVT algorithm of Diehl & Statler (2007).

CIAO must be initialized before starting the script.

For usage information, run the make_maps.py script without arguments or as "make_maps.py --help".

Available models

By default, the script fits a WABS * MEKAL model to each spectrum. A second component can be added using the "--add_comp=component" argument, where component is one of the following:

  • mekal/apec: add a 2nd single-temperature component (WABS*[MEKAL + MEKAL]). The abundances of the two single-temperature components are tied together.
  • pow: add a power-law component (WABS*[MEKAL + POW])

If a second component is specified, the fit is performed twice: once for the single-temperature model and again with the second component included. The chi2 values for the two fits are compared in each region. If the fit for a given region improves significantly with the second component included (from an F-test with a null probability of 0.05), the two-component fit is used in the final maps; otherwise, the single-temperature results are used (if the mapped parameter is not one of the single-temperature model, its value is set to 0.0 when the single-temperature model is preferred).

In the case of the two-temperature model, two maps are made: a low-temperature and a high-temperature map. If the single-temperature fit is preferred in this case, its value of the temperature is used in both maps. In all cases when a second component is specified, an F-test probability map is made.

Spectral parameters that can be mapped

The following parameters can be mapped (by passing them to make_maps.py with the --vars_to_map argument; e.g., --vars_to_map="kT, Z, fkT"):

  • kT / fkT: MEKAL or APEC temperature / error (keV)
  • Z / fZ: MEKAL or APEC abundance / error (Solar)
  • nH / fnH: WABS column density / error (10^22 cm^-2)
  • norm / fnorm: MEKAL or APEC normalization / error
  • chi2: chi-squared value of the fit
  • plindx / fplindx: power-law index / error; requires "--add_comp=pow"

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Python scripts to make maps of spectral parameters with Chandra data

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